PROJECT SUMMARY: PROJECT 3 The purpose of PROJECT 3 is to determine how failures in information processing that supports state representation in neural circuits relate to clinical heterogeneity in early psychosis. To this end, we will: (a) Recruit people with early psychosis (N=125) and demographically similar healthy controls (N=125) aged 16-30 years; (b) Determine test-retest reliability of the DPX and Bandit tasks as assessments of state representation processes; (c) Characterize behavioral performance and neurophysiology at baseline using the DPX and Bandit tasks during simultaneous EEG-fMRI; (d) Follow patients for 6 months while they receive usual care, to delineate their clinical trajectories; (e) Repeat the behavioral and EEG-fMRI assessments after six months (N=100 retained per group). The data we acquire will allow us to examine the baseline relationships between clinical and experimental measures, and also to investigate how changes in clinical and experimental measures are related over a 6-month time period during a critical phase of illness. The overall goal of PROJECT 3 is to permit neural macro-circuit links in humans to the behavioral and neurophysiology experiments in monkeys and mice (PROJECTS 1 & 2). This will allow us to examine how state representation dysfunctions observed in early psychosis -- along with EEG and fMRI-derived neurophysiologic indices of activity timing, excitatory-inhibitory (E-I) balance, and noise -- relate to clinical heterogeneity at baseline, and to heterogeneity in 6-month clinical trajectories. In Aim 1, we compute the retest reliability of state representation measures. In Aim 2, we characterize and compare the features of behavior, EEG and fMRI in early psychosis and healthy controls during state representation processes. In Aim 3,we re- assess performance on the DPX and Bandit tasks during simultaneous EEG-FMRI, in order to characterize the course of state representation dysfunctions in early psychosis during the critical first 6 months of treatment. We will determine the extent to which changes in computational parameters derived from the COMPUTATIONAL CORE, and neurophysiologic measures related to activity timing, E-I balance, and noise (see TRANSLATIONAL NEUROPHYSIOLOGY CORE), map to distinct trajectories in quality of life using causal discovery analyses. We will also test whether trajectories can be predicted from baseline features. Additionally, our healthy control data set will permit us to explore normal patterns of stability vs. change as observed over 6 months in adolescents and young adults.